President Obama on Future of AI and Tech, Bots Label Video, More – This Week in Artificial Intelligence 10-14-16

Daniel Faggella is the founder and CEO at Emerj. Called upon by the United Nations, World Bank, INTERPOL, and many global enterprises, Daniel is a sought-after expert on the competitive strategy implications of AI for business and government leaders.

President Obama was generous enough to take time out of his (still) busy schedule to guest-edit Wired’s November issue, also contributing an opening essay that articulates his thoughts on why this is the best time to be alive (regardless of what’s touted in news and social media) and how he sees our current and future generations continuing to make leaps in scientific and technological progress. In his goal for the issue, he says,

That’s why I centered this issue on the idea of frontiers—stories and ideas about what’s over the next horizon, about what lies on the other side of the barriers we haven’t broken through yet.

He names just a few of the challenges we still need to work together to solve – climate change; economic inequality; cybersecurity; cancer and antibiotic-resistant superbugs – and emphasizes the positive gains made in focusing on STEM education and the democratization of technology and knowledge to reach citizens outside the walls of MIT and other research universities. His vision of an emboldened, pioneering era of Americans is not new in principle, though an evolving socio-cultural environment and technological tools go hand-in-hand with his message, which is worth reading.

2 – Silicon Valley Makes Big Strides in AI, While the Government Ponders its Future

In the progressive discussions around AI, there are disagreements and governing forces with potentially differing interests at the helm. Actions and sometime opposing messages continue to flow out of two of the most influential players – Silicon Valley powerhouses (like Google, Apple, and others), and the U.S. government. The White House, which has increasingly become invested in this arena, released a new report on Wednesday outlining the administration’s focus on future potentials and challenges inherent in the inevitable progress of artificial intelligence. The report focuses on current applications (like self-driving vehicles) and spotlights public policy considerations in light of these evolving technologies; the announcement makes note of a companion strategic plan for federally-funded research that was released alongside the report. As the government and SV players continue their trajectories, there will continue to be friction and debate in how quickly (and at what costs) AI is being developed both in and out of the private sector.

Two National Tsinghua University professors, collaborating with a Microsoft researcher, have used deep learning to further develop machine’s abilities to generate relevant titles and tags based on video content. Professors Chia-Wen Lin and Min Sun were first inspired by Microsoft’s COCO (Common Objects in Context), a new image recognition, segmentation, and captioning dataset; they collaborated with Microsoft Research Asia’s Dr. Tao Mei to use COCO captions for sentence augmentation and captions to train their system, in which a bot highlights important moments within video and comes up with suggestions for an appropriate title and captions. Their work furthers the ultimate goal of a comprehensive visual, artificial intelligence that understands and can categorize content in video.

Robots have historically been used in manufacturing because they’re adept at handling stiff, heavy objects, but when it comes to more dexterous and delicate tasks – not so much. Now, one tech-forward entrepreneur has created a robotic system that can sew a T-shirt from beginning to end. Jonathan Zornow’s “Sewbo” starts with a temporarily-stiffened fabric that makes it easy for a robot to work. Zornow will be using his programmable robotic arm in an upcoming partnership with Bluewater Defense, which makes combat trousers for the U.S. military. Bluewater’s CEO Eric Spcakey said,

“It requires 64 [manufacturing] operations just to make a single combat trouser. If we can automate every 2 to 3 of those, it will make the process much more efficient.”

It may not be too long before automated sewing robots make their way into the broader textile industry.

Host Charlie Rose hosted a timely 60 Minutes segment titled Artificial Intelligence, which aired on October 9 that took a closer look at the status of AI today and the minds and billions of dollars that have made this progress possible over the last decade. Rose interviewed figures such as John Kelly, head of research at IBM; Dr. Ned Sharpless, who runs the cancer center at North Carolina at Chapel Hill; Andrew Moore, former Google employee and head of the Computer Science department at Carnegie Mellon; among others. One of the overarching ideas being explored is that AI has, in some ways, shown levels of creativity and judgement-making that exceeds human beings, and that this evolution doesn’t look to be slowing down anytime soon.

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In 1956, ten of the world's leading electrical engineers convened on the burgeoning topic of "Artificial Intelligence" - which was far from being recognized as a field. A decade later, the progress of early AI efforts had some researchers envisioning a relatively easy glide to human-level intelligence in machines.

Cancer cells have found new foes in AI and the Nordic countries. In just the passed month, both Sweden’s Uppsala University (UU) and the Technical University of Denmark (DTU) have announced systems that accelerate cancer treatment research and diagnoses. By joining genetics with computer science researchers at the DTU have developed a self-learning computer program that can successfully locate the disease 85 percent of the time. Meanwhile UU’s "new smart research robot” assists doctors in finding optimal cancer treatment combinations for their patients.

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In 1956, ten of the world's leading electrical engineers convened on the burgeoning topic of "Artificial Intelligence" - which was far from being recognized as a field. A decade later, the progress of early AI efforts had some researchers envisioning a relatively easy glide to human-level intelligence in machines.

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